CN106846262A - Remove the method and system of mosquito noise - Google Patents

Abstract

The present invention relates to a method and system for removing mosquito noise. The method for removing mosquito noise includes: when determining that an area block to be processed is an edge block, determining the neighbors of the area block to be processed in an azimuth direction Whether there are mosquito noise blocks and flat blocks continuously in the domain block; when it is determined that there are mosquito noise blocks and flat blocks, it is determined that the area block to be processed is located in the mosquito noise area; the edge block probability of the area block to be processed is obtained respectively , and the mosquito noise block probability and the flat block probability of its adjacent area blocks, select the minimum value as the mosquito noise filter weight; use the mosquito noise filter weight to process the area in the mosquito noise area blocks for mosquito noise filtering. In the present invention, it is realized how to simplify the detection of mosquito noise and effectively remove the mosquito noise between the background and the object while protecting the texture area to the greatest extent.

Description

Method and system for removing mosquito noise

technical field

The present invention relates to the technical field of video image processing, in particular to the technology of removing mosquito noise, in particular to a method and system for removing mosquito noise.

Background technique

The Video Reference Impairment System project group defines mosquito noise as "distortion along the edges of moving objects, manifested as a layer of flying objects or fuzzy bubbles around the object (like mosquitoes flying around a person's head and shoulders) ". Mosquito noise occurs when an image is reconstructed and some data is discarded due to the use of an inverse cosine transform.

Mosquito noise often appears in the transition area between edge blocks and flat blocks, combined with this feature, mosquito noise can be detected. Existing methods for detecting mosquito noise mainly include: airspace methods, frequency domain methods, and methods combining airspace and frequency domains.

In the method of combining the space domain and the frequency domain, one of the ways is to use the method of SAD (sum of absolute difference, the sum of the absolute value of the difference) in the regional block to obtain the space domain feature, and the frequency domain method uses the DCT transform method to obtain the frequency domain feature . Both methods combine the information of the surrounding M*N area blocks to determine whether the current area block is a mosquito noise block. In the space domain method, the edge can be detected very well, but the distinction between the texture area and the mosquito noise area largely depends on the size of the selected area block. If the size of the area block is reduced, it will affect the final low-pass filter device, resulting in residual visible noise; among them, the frequency domain method detects rough edges. Compared with the spatial domain method, the frequency domain can distinguish mosquito noise and texture areas very well.

Therefore, if only the space domain method is used, the weak texture area will be blurred, and only the frequency domain method is used, and the mosquito noise near the edge cannot be removed because some edges cannot be detected.

In the method of combining space domain and frequency domain, another way is to use the DCT method to find edge blocks, and then use the variance method to divide the edge blocks into three categories. For each case, 3D bilateral filtering is performed in combination with quantization constraint coefficients. This method needs 100 candidate quantization tables, and has high complexity, occupying a lot of hardware resources.

Contents of the invention

In order to solve the above-mentioned problems in the prior art, that is, how to simplify the detection of mosquito noise and effectively remove the mosquito noise between the background and the object while protecting the texture area to the maximum extent, the present invention provides a Methods for removing mosquito noise include:

When determining that the area block to be processed is an edge block, determine whether there are mosquito noise blocks and flat blocks continuously in the neighborhood blocks of the area block to be processed in an azimuth direction;

When it is determined that there is a mosquito noise block and a flat block, it is determined that the area block to be processed is located in a mosquito noise area;

Respectively obtain the edge block probability of the block to be processed, the mosquito noise block probability and the flat block probability of its adjacent block, and select the minimum value as the mosquito noise filtering weight;

Using the mosquito noise filtering weights to perform mosquito noise filtering processing on the to-be-processed area block located in the mosquito noise area.

Preferably, determining that the area block to be processed is an edge block specifically includes:

Calculate the probability that all pixels in the block to be processed are edge points;

Determining that the mean of the probability that all pixels are edge points is the edge block probability of the block to be processed;

When the edge block probability of the area block to be processed is greater than a preset threshold, it is determined that the area block to be processed is an edge block.

Preferably, the determining whether there are mosquito noise blocks and flat blocks continuously in the neighborhood blocks of the area block to be processed in an azimuth direction, specifically includes:

Taking the area block to be processed as a starting point, selecting two neighboring blocks successively adjacent to it in each azimuth direction, and calculating the mosquito noise block probability that the first adjacent block is a mosquito noise block, and The flat block probability that the second adjacent block is a flat block;

determining whether the first neighborhood block is a mosquito noise block according to the mosquito noise block probability;

Determine whether the second neighboring block is a flat block according to the flat block probability.

Preferably, using the mosquito noise filtering weight to perform mosquito noise filtering on the area block to be processed located in the mosquito noise area, specifically includes:

Select any pixel in the block to be processed, select a preset number of adjacent pixels in the row where the pixel is located and a preset number of adjacent pixels in the column where the pixel is located, according to each pixel's The pixel value and the mosquito noise filtering weight are calculated to obtain the mosquito noise filtering result.

Preferably, the mosquito noise filtering result is calculated according to the pixel value of each pixel point and the mosquito noise filtering weight, through the following formula:

Y _out ＝(1-P _Sigma )×Y _cur +P _Sigma ×Y _filt

Wherein, Y _out is the luminance value of the selected pixel point output in the region block to be processed, P _Sigma is the mosquito noise filter weight, and Y _cur is the input value of the selected pixel point in the region block to be processed Pixel value, Y _filt is the sigma filtering result of the pixels selected in the block to be processed.

Preferably, the Y _filt is specifically calculated by the following formula:

Wherein, _Wij is the weight of the absolute value of the pixel value of the pixel selected in the region block to be processed and the pixel value of its adjacent pixel, and diff is the pixel selected in the region block to be processed The absolute value of the pixel value of the pixel value and the pixel value of its adjacent pixel point, Y _ij is the pixel value of the adjacent pixel point of the selected pixel point in the area block to be processed, and I is the pixel value in the area block to be processed The value range of the row where the selected pixel is located, and J is the value range of the column where the selected pixel is located in the block to be processed.

The present invention also provides a system for removing mosquito noise, comprising:

The first processing unit is configured to determine whether there are mosquito noise blocks and flat blocks in the neighborhood blocks of the block to be processed in an azimuth direction when it is determined that the block to be processed is an edge block;

The second processing unit is used to determine that the area block to be processed is located in the mosquito noise area when it is determined that there are mosquito noise blocks and flat blocks;

The selection unit is used to obtain the edge block probability of the block to be processed, the mosquito noise block probability and the flat block probability of its adjacent block, and select the minimum value as the mosquito noise filtering weight;

The third processing unit is configured to use the mosquito noise filtering weight to perform mosquito noise filtering on the area block to be processed located in the mosquito noise area.

Preferably,

The first processing unit is specifically used to calculate the probability that all pixels in the block to be processed are edge points; determine that the mean of the probabilities of all pixels as edge points is the edge block probability of the block to be processed ; When the edge block probability of the area block to be processed is greater than a preset threshold, determine that the area to be processed is an edge block.

Preferably,

The first processing unit is further specifically configured to take the block to be processed as a starting point, select two adjacent adjacent blocks in each azimuth direction, and calculate the first adjacent block as the The mosquito noise block probability of the noise block, and the flat block probability of the second neighbor block being a flat block; determine whether the first neighborhood block is mosquito noise according to the mosquito noise block probability block; determining whether the second neighborhood block is a flat block according to the flat block probability.

Preferably,

The third processing unit is specifically configured to select any pixel in the block to be processed, and select a preset number of adjacent pixels in the row where the pixel is located and a preset number of adjacent pixels in the column where the pixel is located. Neighboring pixels, according to the pixel value of each pixel and the weight of mosquito noise filtering, the mosquito noise filtering result is obtained.

Compared with the prior art, the present invention has at least the following advantages:

Through the design of the present invention, the detection of mosquito noise is simplified while the texture area is protected to the greatest extent, and the mosquito noise between the background and the object is effectively removed.

Description of drawings

Figure 1 is a schematic diagram of the position of the mosquito noise area in the flat area and the texture area;

Fig. 2 is a schematic flow sheet of the method for removing mosquito noise provided by the present invention;

Fig. 3 is the block diagram of the method for removing mosquito noise based on frequency domain and space domain provided by the present invention;

Fig. 4 is wherein the schematic diagram of the horizontal coefficient and the vertical coefficient of Sobel provided by the present invention;

Fig. 5 is a schematic diagram of the marginal probability calculation curve provided by the present invention;

Fig. 6 is a schematic diagram of the neighborhood range of the current block provided by the present invention and the azimuth direction to be calculated;

Fig. 7 is a schematic diagram of the parameters of the 2D-DCT coefficient matrix provided by the present invention;

Fig. 8 is a schematic diagram of the calculation curve of the probability that the area block to be processed is located in the mosquito noise area provided by the present invention;

Fig. 9 is a schematic diagram of the calculation curve of the probability that the area block to be processed is located in the flat area provided by the present invention;

Fig. 10 is a schematic diagram of a diff-Weight calculation curve in the Sigma filter provided by the present invention.

detailed description

Preferred embodiments of the present invention are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention, and are not intended to limit the protection scope of the present invention.

Due to the limitation of network bandwidth, the image signal needs to be encoded, which introduces mosquito noise, resulting in a decrease in the image quality of the image signal. Mosquito noise tends to appear in flat or low-frequency regions next to object edge regions (textured regions), as shown in Figure 1.

As shown in Figure 2, the method for removing mosquito noise provided by the present invention specifically includes:

Step 201, when it is determined that the area block to be processed is an edge block, determine whether there are mosquito noise blocks and flat blocks continuously in the neighborhood blocks of the area block to be processed in one azimuth direction.

In this step, it is determined that the area block to be processed is an edge block, specifically including:

Calculate the probability that all pixels in the area block to be processed are edge points; determine that the mean value of the probability of all pixels being edge points is the edge block probability of the area block to be processed; when the edge of the area block to be processed When the block probability is greater than the preset threshold, it is determined that the area to be processed is an edge block.

The determining whether there are mosquito noise blocks and flat blocks continuously in the neighborhood blocks of the area block to be processed in an azimuth direction, specifically includes:

Taking the area block to be processed as a starting point, selecting two neighboring blocks successively adjacent to it in each azimuth direction, and calculating the mosquito noise block probability that the first adjacent block is a mosquito noise block, and The flat block probability that the second adjacent block is a flat block;

determining whether the first neighborhood block is a mosquito noise block according to the mosquito noise block probability;

Determine whether the second neighboring block is a flat block according to the flat block probability.

This step can also adopt the framework shown in Figure 3, in this framework,

Among them, the spatial edge detection unit

Use the Sobel Sobel algorithm to calculate the edge block probability, where the horizontal and vertical coefficients of Sobel are shown in Figure 4.

The absolute value of the results of the two azimuth directions after Sobel filtering is summed to obtain the edge amplitude gradAmp, and then the probability P _{pixel_edge} that the pixel point is an edge point is obtained through the curve shown in Figure 5 .

Calculate the probability P _{block_edge} of the edge block by taking the mean value of all pixels P _{pixel_edge} in the area block of 4*4 size; if P _{block_edge} is greater than the preset threshold, the current area block is an edge block and needs to be detected The information of the surrounding neighborhood blocks, the distribution of the neighborhood blocks is shown in Figure 6, where the number 13 represents the current edge block.

Frequency Domain Feature Detection Unit

Through the 2D-DCT method, the frequency domain characteristics of neighboring blocks other than the current block are obtained. The formula is as follows:

^Y =AXAT

The DCT matrix A coefficient is shown in Figure 7, and X is a 4*4 matrix of the current block. Then take the sum U _n of Y except the other numbers in the upper right corner as the frequency domain characteristic of the block.

Neighborhood information combination judgment unit

Detect whether there are texture blocks, mosquito noise blocks and flat blocks continuously in each azimuth direction; use the edge block probability to represent the texture block probability. Each azimuth direction is shown as the arrow in Figure 5, and there are 8 directions in total (the eight azimuth directions include, due east azimuth direction, due south azimuth direction, due west azimuth direction, due north azimuth direction, southeast azimuth direction, southwest Azimuth direction, northwest azimuth direction and northeast azimuth direction), note that the azimuth direction here is the direction pointed by the arrow, such as 13->7->1 and 13->19->25 are two different azimuth directions.

According to the curve shown in Figure 8, the probability that the block to be processed is located in the mosquito noise area is calculated; the abscissa is the DCT frequency domain characteristic U _n of the block to be processed, and the ordinate P _mos is the probability that the block to be processed is a mosquito noise block . m_flat, m_mos1, m_mos2, and m_tex are all threshold constants. The probability that the block to be processed is located in a flat block is calculated according to the curve shown in FIG. 9 . The abscissa is the DCT frequency domain characteristic U _n of the region block to be processed, and the ordinate P _flat is the probability that the region block to be processed is a flat block. Both f_flat and f_mos are threshold constants.

Step 202, when it is determined that there are mosquito noise blocks and flat blocks, it is determined that the area block to be processed is located in the mosquito noise area.

Step 203, respectively obtain the edge block probability of the area block to be processed, the mosquito noise block probability and the flat block probability of its adjacent area blocks, and select the minimum value among them as the mosquito noise filtering weight.

Take the minimum value of the continuous edge block probability, mosquito noise block probability and flat block probability in a certain direction to obtain the final probability value P _Sigma as the mosquito noise filtering weight.

P _Sigma = min(P _flat , P _mos , P _{block_edge} )

As shown in Figure 5, the P _Sigma in the direction of 13->7->1 is equal to the edge block probability of area block 13, the mosquito noise block probability of area block 7, and the minimum value of the flat block probability of area block 1; and 13 P _Sigma in the ->19->25 direction is equal to the minimum of the edge block probability for region block 13, the mosquito noise block probability for region block 19, and the flat block probability for region block 25.

Step 204, using the mosquito noise filtering weights to perform mosquito noise filtering on the area block to be processed located in the mosquito noise area.

In this step, the mosquito noise filter unit

Mosquito noise filtering is performed on each pixel in the block to be processed.

The filtering method adopts sigma filtering, which specifically performs weighted average according to M×N pixels around each pixel in the area block, such as 3×3, and the result of sigma filtering is Y _filt . The operation process is as follows:

Wherein, W _ij is the weight of the absolute value of the pixel value of the selected pixel in the block to be processed and the pixel value of its adjacent pixel, calculated through the curve shown in Figure 10; diff is the The absolute value (diff=abs(Y _ij -Y _cur )) of the pixel value of the selected pixel point in the processing area block and the pixel value of its adjacent pixel point, Y _ij is selected in the area block to be processed The pixel value of the adjacent pixel of the pixel point, I is the value range of the row where the pixel point is selected in the area block to be processed, and J is the column where the pixel point is selected in the area block to be processed range of values.

The final output brightness value of the current pixel is:

Y _out ＝(1-P _Sigma )×Y _cur +P _Sigma ×Y _filt

Wherein, Y _out is the luminance value output by the pixel point selected in the region block to be processed, Y _cur is the pixel value input by the pixel point selected in the region block to be processed, and Y _filt is the pixel value input in the region block to be processed. The sigma filtering result of the pixels selected in the block to be processed.

The use of the mosquito noise filter weight to perform mosquito noise filter processing on the to-be-processed area block located in the mosquito noise area specifically includes:

Select any pixel in the block to be processed, select a preset number of adjacent pixels in the row where the pixel is located and a preset number of adjacent pixels in the column where the pixel is located, according to each pixel's The pixel value and the mosquito noise filtering weight are calculated to obtain the mosquito noise filtering result.

It can be seen from the foregoing technical solutions that the present invention has the following beneficial effects:

The present invention can find edge points more accurately through the spatial gradient method, avoiding missed detection of some edges; according to the method of frequency domain DCT, it can more accurately distinguish texture and mosquito noise, avoiding the detection of texture as mosquito noise And cause false detection of texture area, or detect mosquito noise area as texture area and cause missed detection of mosquito noise; according to the neighborhood information judgment method, search for mosquito noise in the area where mosquito noise may appear, so that mosquito The noise detection results are more accurate.

Based on the same design as the technical solution provided by the above-mentioned present invention, the present invention also provides a system for removing mosquito noise, including:

The first processing unit is used to determine whether there are mosquito noise blocks and flat blocks in the neighborhood blocks of the block to be processed in an azimuth direction when it is determined that the block to be processed is an edge block; specifically, it is used to calculate and obtain The probability that all pixels in the area block to be processed are edge points; the mean value of the probability of determining that all pixels are edge points is the edge block probability of the area block to be processed; when the edge block probability of the area block to be processed When it is greater than the preset threshold value, it is determined that the area to be processed is an edge block; it is also specifically used to select two neighboring blocks adjacent to each azimuth direction from the block of the area to be processed, and calculate the adjacent blocks The mosquito noise block probability that the first neighborhood block of is a mosquito noise block, and the flat block probability that the second neighbor block is a flat block; the first neighborhood block is determined according to the mosquito noise block probability whether the first neighborhood block is a mosquito noise block; determine whether the second neighborhood block is a flat block according to the flat block probability.

The second processing unit is used to determine that the area block to be processed is located in the mosquito noise area when it is determined that there are mosquito noise blocks and flat blocks;

The selection unit is used to obtain the edge block probability of the block to be processed, the mosquito noise block probability and the flat block probability of its adjacent block, and select the minimum value as the mosquito noise filtering weight;

A third processing unit, configured to use the mosquito noise filtering weight to perform mosquito noise filtering on the area block to be processed located in the mosquito noise area; specifically, to select any pixel point in the area block to be processed , select a preset number of adjacent pixels in the row where the pixel is located and a preset number of adjacent pixels in the column where the pixel is located, and calculate the mosquito pattern according to the pixel value of each pixel and the mosquito noise filtering weight Noise filtering results.

Those skilled in the art should be able to realize that the modules and method steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the electronic hardware and Interchangeability of software. In the above description, the components and steps of each example have been generally described according to their functions. Whether these functions are performed by electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may implement the described functionality using different methods for each particular application, but such implementation should not be considered as exceeding the scope of the present invention.

So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings, but those skilled in the art will easily understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

Claims (10)

1. A method for removing mosquito noise, comprising: When determining that the area block to be processed is an edge block, determine whether there are mosquito noise blocks and flat blocks continuously in the neighborhood blocks of the area block to be processed in an azimuth direction; When it is determined that there is a mosquito noise block and a flat block, it is determined that the area block to be processed is located in a mosquito noise area; Respectively obtain the edge block probability of the block to be processed, the mosquito noise block probability and the flat block probability of its adjacent block, and select the minimum value as the mosquito noise filtering weight; Using the mosquito noise filtering weights to perform mosquito noise filtering processing on the to-be-processed area block located in the mosquito noise area. 2. the method for removing mosquito noise according to claim 1, is characterized in that, determining that the region block to be processed is an edge block, specifically comprises: Calculate the probability that all pixels in the block to be processed are edge points; Determining that the mean of the probability that all pixels are edge points is the edge block probability of the block to be processed; When the edge block probability of the block to be processed is greater than a preset threshold, it is determined that the block to be processed is an edge block. 3. The method for removing mosquito noise according to claim 1, characterized in that, whether there are mosquito noise blocks and flat blocks continuously in the neighborhood block of the said area block to be processed in an azimuth direction, specifically include: Taking the area block to be processed as a starting point, selecting two neighboring blocks successively adjacent to it in each azimuth direction, and calculating the mosquito noise block probability that the first adjacent block is a mosquito noise block, and The flat block probability that the second adjacent block is a flat block; determining whether the first neighborhood block is a mosquito noise block according to the mosquito noise block probability; Determine whether the second neighboring block is a flat block according to the flat block probability. 4. the method for removing mosquito noise according to claim 1, is characterized in that, described utilizing described mosquito noise filtering weight to be positioned at the described area block to be processed of mosquito noise area and carry out mosquito noise filtering process, Specifically include: Select any pixel in the block to be processed, select a preset number of adjacent pixels in the row where the pixel is located and a preset number of adjacent pixels in the column where the pixel is located, according to each pixel's The pixel value and the mosquito noise filtering weight are calculated to obtain the mosquito noise filtering result. 5. the method for removing mosquito noise according to claim 4, is characterized in that, described according to the pixel value of each pixel point and mosquito noise filtering weight calculation obtains mosquito noise filtering result, by following formula: Y _out ＝(1-P _Sigma )×Y _cur +P _Sigma ×Y _filt Wherein, Y _out is the luminance value of the selected pixel point output in the region block to be processed, P _Sigma is the mosquito noise filter weight, and Y _cur is the input value of the selected pixel point in the region block to be processed Pixel value, Y _filt is the sigma filtering result of the pixels selected in the block to be processed. 6. the method for removing mosquito noise according to claim 5, is characterized in that, described Y _filt is specifically calculated by the following formula: ${\mathrm{<span\; class="notranslate">\; Y</span>}}_{\mathrm{<span\; class="notranslate">\; f</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; l</span>}\mathrm{<span\; class="notranslate">\; t</span>}}<span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; I</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; J</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}{\mathrm{<span\; class="notranslate">\; W</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; \&times;</span>{\mathrm{<span\; class="notranslate">\; Y</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; /</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; I</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; J</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}{\mathrm{<span\; class="notranslate">\; W</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}$ Wherein, _Wij is the weight of the absolute value of the pixel value of the pixel selected in the region block to be processed and the pixel value of its adjacent pixel, and diff is the pixel selected in the region block to be processed The absolute value of the pixel value of the pixel value and the pixel value of its adjacent pixel point, Y _ij is the pixel value of the adjacent pixel point of the selected pixel point in the area block to be processed, and I is the pixel value in the area block to be processed The value range of the row where the selected pixel is located, and J is the value range of the column where the selected pixel is located in the block to be processed. 7. A system for removing mosquito noise, comprising: The first processing unit is configured to determine whether there are mosquito noise blocks and flat blocks in the neighborhood blocks of the block to be processed in an azimuth direction when it is determined that the block to be processed is an edge block; The second processing unit is used to determine that the area block to be processed is located in the mosquito noise area when it is determined that there are mosquito noise blocks and flat blocks; The selection unit is used to obtain the edge block probability of the block to be processed, the mosquito noise block probability and the flat block probability of its adjacent block, and select the minimum value as the mosquito noise filtering weight; The third processing unit is configured to use the mosquito noise filtering weight to perform mosquito noise filtering on the area block to be processed located in the mosquito noise area. 8. The system for removing mosquito noise according to claim 7, characterized in that, The first processing unit is specifically used to calculate the probability that all pixels in the block to be processed are edge points; determine that the mean of the probabilities of all pixels as edge points is the edge block probability of the block to be processed ; When the edge block probability of the area block to be processed is greater than a preset threshold, determine that the area to be processed is an edge block. 9. The system for removing mosquito noise according to claim 7, characterized in that, The first processing unit is further specifically configured to take the block to be processed as a starting point, select two adjacent adjacent blocks in each azimuth direction, and calculate the first adjacent block as the The mosquito noise block probability of the noise block, and the flat block probability of the second neighbor block being a flat block; determine whether the first neighborhood block is mosquito noise according to the mosquito noise block probability block; determining whether the second neighborhood block is a flat block according to the flat block probability. 10. the system for removing mosquito noise according to claim 7, is characterized in that, The third processing unit is specifically configured to select any pixel in the block to be processed, and select a preset number of adjacent pixels in the row where the pixel is located and a preset number of adjacent pixels in the column where the pixel is located. Neighboring pixels, according to the pixel value of each pixel and the weight of mosquito noise filtering, the mosquito noise filtering result is obtained.